Frequency-shift super-resolution (SR) microscopy, such as structured illumination microscopy (SIM) and Fourier ptychographic microscopy (FPM), can break the diffraction limit for the imaging of both fluorescently labeled and label-free samples by transferring the high spatial-frequency information into the passband of microscope. However, conventional SIM microscopy systems tend to be bulky and expensive, which limits its applications in various fields. Therefore, we’ve developed some chip-based frequency-shift SR technologies, which is compatible with conventional microscope, and can be further designed for portable imaging systems such as smart phone and so on. We also developed a deep-learning based imaging method to improve the imaging speed of frequency-shift super-resolution microscopy, which enables low-cost and fast super-resolution imaging for real-time live cell biological studies.
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